train_path = 'D:\python\Aclass\yolov5-master\data\coco128\images\\train2017'
test_path = 'D:\python\Aclass\yolov5-master\data\coco128\images\\train2017'
val_path = 'D:\python\Aclass\yolov5-master\data\coco128\images\\train2017'
nc = 2
nc_name = ['heel', 'maid']
weights = 'D:\python\Aclass\yolov5-master\weights\yolov5s.pt'

anchors = [[10,13,16,30,33,23],[30,61,62,45,59,119],[116,90,156,198,373,326]]

gd = 0.33
gw = 0.5
total_batch_size = 2
weight_decay = 0.0005
lr0 = 0.01
momentum = 0.937
epochs = 300
lrf = 0.2
img_size = [416,416]
num_workers = 8
resume = False
logdir = './temp'
noautoanchor = False
anchor_t = 10.0
cls=0.5
image_weights = False
warmup_bias_lr = 0.1
warmup_momentum = 0.8
mosaic = 1.0
mixup = 0.0

degrees = 0
translate=0.1
scale = 0.5
shear = 0
perspective= 0

hsv_h = 0.015
hsv_s = 0.7
hsv_v = 0.4

flipud = 0
fliplr = 0.5

cls_pw = 1.0
obj_pw = 1.0
fl_gamma = 0

giou = 0.05
obj = 1.0

evolve = False
bucket = ''

name = ''
single_cls = False

notest = False

multi_scale = False
nosave = False

backbone=[[-1, 1, 'Focus', [64, 3]],  # 0-P1/2
 [-1, 1, 'Conv', [128, 3, 2]],  # 1-P2/4
 [-1, 3, 'BottleneckCSP', [128]],
 [-1, 1, 'Conv', [256, 3, 2]],  # 3-P3/8
 [-1, 9, 'BottleneckCSP', [256]],
 [-1, 1, 'Conv', [512, 3, 2]],  # 5-P4/16
 [-1, 9, 'BottleneckCSP', [512]],
 [-1, 1, 'Conv', [1024, 3, 2]],  # 7-P5/32
 [-1, 1, 'SPP', [1024, [5, 9, 13]]],
 [-1, 3, 'BottleneckCSP', [1024, False]],  # 9
 ]

head=\
    [[-1, 1, 'Conv', [512, 1, 1]],
   [-1, 1, 'nn.Upsample', [None, 2, 'nearest']],
   [[-1, 6], 1, 'Concat', [1]],  # cat backbone P4
   [-1, 3, 'BottleneckCSP', [512, False]],  # 13

   [-1, 1, 'Conv', [256, 1, 1]],
   [-1, 1, 'nn.Upsample', [None, 2, 'nearest']],
   [[-1, 4], 1, 'Concat', [1]],  # cat backbone P3
   [-1, 3, 'BottleneckCSP', [256, False]],  # 17 (P3/8-small)

   [-1, 1, 'Conv', [256, 3, 2]],
   [[-1, 14], 1, 'Concat', [1]],  # cat head P4
   [-1, 3, 'BottleneckCSP', [512, False]],  # 20 (P4/16-medium)

   [-1, 1, 'Conv', [512, 3, 2]],
   [[-1, 10], 1, 'Concat', [1]],  # cat head P5
   [-1, 3, 'BottleneckCSP', [1024, False]],  # 23 (P5/32-large)

   [[17, 20, 23], 1, 'Detect', [nc, anchors]],  # Detect(P3, P4, P5)
  ]